The Human Impact of Machines
Question: How are algorithms altering human individuals, groups, and societies?
Machines are an integral part of our daily lives. Given that we are markedly shaped by the conditions that surround us, how might our interactions with machines be altering human individuals, groups, and societies? This research group studies the impacts—broadly conceived—that our relationship with machines may be having on the human system.
Principal Investigator(s)
Selected Papers
Groh, M., Epstein, Z., Obradovich, N., Cebrian, M., & Rahwan, I. (2019). Human detection of machine manipulated media. arXiv preprint arXiv:1907.05276.
Obradovich, N.∗,Özack, Ö.∗, Martín, I.∗, Ortuño-Ortín, I., Awad, E., Cebrian, M.,Cuevas, R., Desmet, K., Rahwan, I., Cuevas, Á. (2020). Expanding the measurement of culture with a sample of two billion humans. (NBER). (∗ denotes equal contribution).
Bonnefon, J. F., & Rahwan, I. (2020). Machine Thinking, Fast and Slow. Trends in Cognitive Sciences. 24(12):1019–1027
Rahwan, I., Crandall, J. W., & Bonnefon, J. F. (2020). Intelligent machines as social catalysts. Proceedings of the National Academy of Sciences, 117(14), 7555-7557.
Serna, I., Morales, A., Fierrez, J., Cebrian, M., Obradovich, N., and Rahwan, I. (2020). Algorithmic discrimination: Formulation and exploration in deep learning-based face biometrics. Proceedings of the Workshop on Artificial Intelligence Safety (SafeAI 2020).
Serna, I., Morales, A., Fierrez, J., Cebrian, M., Obradovich, N., and Rahwan, I. (2020). SensitiveLoss: Improving accuracy and fairness of face representations with discrimination-aware deep learning. (arXiv)
Mir, R., Felbo, B., Obradovich, N., and Rahwan, I. (2019). Evaluating style transfer for text. Annual Conference of the North American Chapter of the Association for Computational Linguistics.
Rahwan, I.∗, Cebrian, M.∗, Obradovich, N.∗ et al. Machine behaviour. Nature 568, 477–486 (2019). https://doi.org/10.1038/s41586-019-1138-y (∗ denotes equal contribution).
Ishowo-Oloko, F., Bonnefon, J., Soroye, Z. et al. Behavioural evidence for a transparency–efficiency tradeoff in human–machine cooperation. Nat Mach Intell1, 517–521 (2019). https://doi.org/10.1038/s42256-019-0113-5
Crandall, J.W., Oudah, M., Tennom et al. Cooperating with machines. Nat Commun 9, 233 (2018). https://doi.org/10.1038/s41467-017-02597-8
Garcia, D., Kassa, Y. M., Cuevas, A., Cebrian, M., Moro, E., Rahwan, I., & Cuevas, R. (2018). Analyzing gender inequality through large-scale Facebook advertising data. Proceedings of the National Academy of Sciences, 115(27), 6958-6963.
Epstein, Z., Payne, B.H., Shen, J.H., Hong, C.J., Dubey, A., Felbo, B., Groh, M., Obradovich, N., Cebrian, M., and Rahwan, I. (2018). TuringBox: An experimental platform for the evaluation of AI systems. International Joint Conference on Artificial Intelligence (IJCAI). Demo Track.
Epstein, Z., Payne, B.H., Shen, J.H., Dubey, A., Felbo, B., Groh, M., Obradovich, N.,Cebrian, M., and Rahwan, I. (2018). Closing the AI knowledge gap. (arXiv).